Fibrobacter succinogenes is a cellulolytic predominant rumen bacterium that plays an essential role in the degradation of plant fibers in the rumen ecosystem. This bacterium converts cellulose polymers into intracellular glycogen and the fermentation metabolites succinate, acetate and formate. We reconstructed the genome scale metabolic network of the strain S85 of F. succinogenes using the Automatic Reconstruction of metabolic models (AuReMe) workspace. A first draft was reconstructed by annotation using Pathwaytools. The obtained draft model was enhanced using 5 external bacterial metabolic models by orthology-based reconstruction then gap-filled and curated manually for maximizing the biomass reaction flow. Adenosylcobalamin synthesis, glycogen metabolism, ammonium assimilation and the catabolism of glucose pathways were particularly investigated and completed with high-quality manual curation. The final network was achieved with a gene-reaction association for added reactions with high gene similarity based on BLASTP results. The F. succinogenes S85 metabolic network comprises 1314 genes, 1567 metabolic reactions, 1588 unique metabolites and 931 pathways. Genome annotation identified 623 reactions and manual curation, gap filling and orthology, respectively added 462, 105 and 174 reactions. The biomass reaction flow consisting of essential seeds and targets needed for F. succinogenes growth included 136 reactions. The resulting network is a useful resource for investigating the metabolic capabilities of F. succinogenes S85. We will further exploit the metabolic network to construct a dynamic model of microbial metabolism. Such an approach is a key step towards the integration of omic microbial information into predictive models of rumen metabolism.